English

Gaussian integrability of distance function under the Lyapunov condition

Probability 2015-02-17 v2

Abstract

In this note we give a direct proof of the Gaussian integrability of distance function as μeδd2(x,x0)<\mu e^{\delta d^2(x,x_0)} < \infty for some δ>0\delta>0 provided the Lyapunov condition holds for symmetric diffusion Markov operators, which answers a question proposed in Cattiaux-Guillin-Wu [6, Page 295]. The similar argument still works for diffusions processes with unbounded diffusion coefficients and for jump processes such as birth-death chains. An analogous discussion is also made under the Gozlan's condition arising from [9, Proposition 3.5].

Keywords

Cite

@article{arxiv.1409.8496,
  title  = {Gaussian integrability of distance function under the Lyapunov condition},
  author = {Yuan Liu},
  journal= {arXiv preprint arXiv:1409.8496},
  year   = {2015}
}

Comments

11 pages, published, ECP. Some extensions to unbounded diffusions and jump processes have been added, and two referees' suggestions incorporated